CN112173997A - Intelligent folding arm crane safety early warning and control system and method based on cloud side end data fusion - Google Patents

Intelligent folding arm crane safety early warning and control system and method based on cloud side end data fusion Download PDF

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CN112173997A
CN112173997A CN202011058554.9A CN202011058554A CN112173997A CN 112173997 A CN112173997 A CN 112173997A CN 202011058554 A CN202011058554 A CN 202011058554A CN 112173997 A CN112173997 A CN 112173997A
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crane
leg
early warning
arm
landing
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CN112173997B (en
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张燕军
韩甲文
李文峰
卞隆元
张永超
陈兆勇
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Jiangsu Hongchang Tianma Logistics Equipment Co ltd
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Jiangsu Hongchang Tianma Logistics Equipment Co ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C23/00—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes
    • B66C23/62—Constructional features or details
    • B66C23/72—Counterweights or supports for balancing lifting couples
    • B66C23/78—Supports, e.g. outriggers, for mobile cranes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C13/00—Other constructional features or details
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C13/00—Other constructional features or details
    • B66C13/18—Control systems or devices
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C15/00—Safety gear
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C15/00—Safety gear
    • B66C15/06—Arrangements or use of warning devices
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C23/00—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes
    • B66C23/62—Constructional features or details
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C23/00—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes
    • B66C23/62—Constructional features or details
    • B66C23/64—Jibs
    • B66C23/68—Jibs foldable or otherwise adjustable in configuration

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  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Jib Cranes (AREA)

Abstract

An intelligent folding arm crane safety early warning and control system and method based on cloud side end data fusion. The field of crane machinery is related to, and especially relates to a folding arm crane intelligent safety early warning and control system and method based on cloud side end data fusion. The folding arm crane intelligent safety early warning and control system and method based on cloud side end data fusion are convenient to detect and early warn. The crane system comprises a base, a rotating assembly, a supporting leg assembly and an extending arm assembly, wherein the rotating assembly is arranged on the base and comprises a rotating table, and the acquisition module, the tension sensor, the angle sensor and the four pressure sensors are respectively connected with the cloud platform through an NB-IOT transmission module; the cloud platform is connected with the mobile phone for early warning. The invention improves the safety and stability of the crane in the working operation on the inclined plane.

Description

Intelligent folding arm crane safety early warning and control system and method based on cloud side end data fusion
Technical Field
The invention relates to the field of crane machinery, in particular to a folding arm crane intelligent safety early warning and control system and method based on cloud side end data fusion.
Background
With the rapid development of the number of cranes in China, the infrastructure construction in China is greatly promoted, but a crane overturn prevention system is an important guarantee for the operation safety of cranes. The crane which runs stably on the flat ground has the risk of overturning in certain uneven mountainous areas, the overturning prevention of the traditional crane is carried out on the flat ground, the crane which is a special working operation vehicle is often used for mountainous areas with frequent earthquakes, potential safety hazards exist, the reliability detection in the working process of the crane needs to be further improved, and therefore the technology which can be used for carrying out early warning on the overturning prevention detection by utilizing the technology of the internet of things is especially important.
Disclosure of Invention
Aiming at the problems, the invention provides the intelligent folding arm crane safety early warning and control system and method based on cloud side end data fusion, which are convenient to detect and early warn.
The technical scheme of the invention is that the device comprises a crane system and a detection system, wherein the crane system comprises a base, a rotating assembly, a supporting leg assembly and an extending arm assembly,
the rotating assembly is arranged on the base and comprises a rotating platform,
the supporting leg assembly is arranged at two ends of the base and comprises four supporting legs which are respectively a left front supporting leg, a right front supporting leg, a left rear supporting leg and a right rear supporting leg,
the left front leg comprises a left front extension part and a left front ground falling part,
the right front leg includes a right front extension and a right front landing section,
the left rear leg comprises a left rear extension part and a left rear floor part,
the right rear leg comprises a right rear extension part and a right rear landing part,
the extension arm assembly is arranged on one side of the rotating platform and comprises an extension arm, a drag hook and a drag rope, and the drag hook is connected with the extension arm through the drag rope;
the detection system comprises a cloud platform, an acquisition module, an NB-IOT transmission module, a level meter, a tension sensor, an angle sensor and four pressure sensors,
the acquisition module is used for acquiring the motion state of the crane;
the gradienter is arranged on the rotating platform;
the tension sensor is arranged on the inhaul cable;
the angle sensor is used for acquiring an included angle between the inhaul cable and the extending arm;
the four pressure sensors are respectively arranged on the grounding end of the left front grounding part, the grounding end of the right front grounding part, the grounding end of the left rear grounding part and the grounding end of the right rear grounding part;
the acquisition module, the tension sensor, the angle sensor and the four pressure sensors are respectively connected with the cloud platform through the NB-IOT transmission module; the cloud platform is connected with the mobile phone for early warning.
A crane overturn prevention detection method based on an Internet of things cloud platform comprises the following steps:
s1, establishing a coordinate system;
s2, respectively acquiring data through the acquisition module, the tension sensor, the angle sensor and the four pressure sensors, and connecting the data with the cloud platform through the NB-IOT transmission module for analysis and judgment; and after the overturning condition is met, carrying out mobile phone early warning.
In step S1, the lowest point of the four legs of the crane is used as the origin O of the coordinate system, and the projection of the vertical axis of the level in the crane in the horizontal direction is the X axis, so that the four legs are distributed left and right, wherein the horizontal plane is the Z axis, the plane perpendicular to the XOZ plane is the Y axis, and the tilt amounts of the X and Y axes measured by the level are θ1，θ2The bubble direction of the level meter is the positive direction;
and changing the coordinate system into a Cartesian coordinate system through matrix transformation, wherein the left-hand rotation matrix of the crane moving in the Cartesian coordinate system is the actual motion state.
In the step S2, in the step S,
the pressure sensors below the four support legs send data information through the NB-IOT transmission module;
the weight of the heavy object lifted by the drag hook is marked as G through the tension sensor, and the self weight of the crane is G1Decomposing on the X 'OY' plane, calculating the overturn of the X 'axis and the Y' axis,
the extension length of the extension arm is d, the distance between the left front leg and the right front leg is d1, the distance between the right front leg and the right rear leg is d2,
reading an angle beta between the extending arm and the Y' axis through the acquisition module, connecting the angle information and the gravity of the heavy object to the cloud platform through the NB-IOT transmission module, and analyzing the overturning of the crane through the cloud platform;
wherein, the analysis judgment mode is as follows:
the angle between the weight and the projecting arm is measured by the angle sensor as alpha, in the Y' axis direction, the projecting arm is | dcos β |,
when the cos beta of the cloud platform is positive, the gravity component is Gcos theta2The moment arm interval is
Figure BDA0002711607610000021
When in use
Figure BDA0002711607610000031
The supporting legs are supported at the moment and are respectively a right front landing part and a right rear landing part, and the pressure of the pressure sensor of the left front supporting leg landing part and the pressure of the left rear supporting leg landing part are detected simultaneouslyWhen the force sensor is 0, judging that the crane overturns, and giving out early warning;
early warning of Y ' direction overturn, in the X ' axis direction, extending arm | dsin beta |, then analyzing on the X ' axis, the gravity component is Gcos theta1The extension arm is an X' axis component | dsin beta |, when the detected crane rotation angle beta data is transmitted to the cloud platform through the NB-IOT transmission module and is judged to be 0-180 degrees, the weight gravity component is Gcos theta1The moment arm interval is
Figure BDA0002711607610000032
The gravity component of the crane is G1cosθ1The gravity force arm of the crane is
Figure BDA0002711607610000033
When in use
Figure BDA0002711607610000034
When the pressure of the pressure sensor of the landing part of the left rear leg and the pressure sensor of the landing part of the right rear leg are 0, an X' axial overturn early warning is sent out;
when the detected crane rotation angle beta data is transmitted to the cloud platform through the NB-IOT transmission module and is judged to be 180 degrees and 360 degrees, the weight gravity component is Gcos theta1The distance between the force arms of the weights is
Figure BDA0002711607610000035
The gravity component of the crane is G1cosθ1The gravity force arm of the crane is
Figure BDA0002711607610000036
When in use
Figure BDA0002711607610000037
The supporting legs are a left rear leg landing part and a right rear leg landing part, a pressure sensor of the left front leg landing part and a pressure sensor of the right front leg landing part are detected simultaneously, and when the left front leg landing partThe pressure of the pressure sensor at the ground falling part of the right front supporting leg and the pressure of the pressure sensor at the ground falling part of the right front supporting leg are 0, and an overturning early warning is sent out.
The method has clear calculation and a clear structure, the data collected by the collection module, the tension sensor, the angle sensor and the four pressure sensors are transmitted to the cloud platform for overturning simulation calculation by utilizing NB-IOT internet of things data transmission, and when the calculation result shows that the overturning risk exists, early warning is carried out through the mobile phone end, so that the safety and the stability of the crane in the inclined plane for working operation are improved.
Drawings
FIG. 1 is a schematic view of a coordinate system of a crane according to the present invention,
figure 2 is a front elevation view of a crane ramp in the present invention,
FIG. 3 is a schematic diagram of a detection system of the present invention;
in the figure, 1 is front left leg portion ground pressure sensor, 2 is front right leg portion ground pressure sensor, 3 is rear left leg portion ground pressure sensor, 4 is rear right leg portion ground pressure sensor, 5 is the spirit level, 6 is the base, 7 is rotatory assembly, 8 is front left leg portion ground, 9 is right leg portion ground, 10 is rear left leg portion ground, 11 is rear right leg portion ground, 12 is the cantilever arm, 13 is the cable, 14 is the drag hook, 15 is angle sensor.
Detailed Description
The present invention, as shown in fig. 1-3, includes a crane system and a detection system, the crane system includes a base 6, a rotation assembly 7, a leg assembly and a boom assembly,
the rotating assembly 7 is arranged on the base and comprises a rotating platform,
the supporting leg assembly is arranged at two ends of the base and comprises four supporting legs which are respectively a left front supporting leg, a right front supporting leg, a left rear supporting leg and a right rear supporting leg,
the left front leg comprises a left front extension part and a left front landing part 8,
the right front leg includes a right front extension and a right front landing 9,
the left rear leg comprises a left rear extension and a left rear landing part 10,
the right rear leg includes a right rear projecting portion and a right rear land portion 11,
the extension arm assembly is arranged on one side of the rotating platform and comprises an extension arm 12, a drag hook 14 and a drag rope 13, and the drag hook is connected with the extension arm through the drag rope;
the detection system comprises a cloud platform, an acquisition module, an NB-IOT transmission module, a level 5, a tension sensor, an angle sensor 15 and four pressure sensors,
the acquisition module is used for acquiring the motion state of the crane;
the gradienter 5 is arranged on the rotating platform;
the tension sensor is arranged on the inhaul cable;
the angle sensor 15 is used for acquiring an included angle between the inhaul cable and the extending arm; the measuring end of the angle sensor is fixed with the inhaul cable;
the four pressure sensors are respectively arranged on the grounding end of the left front grounding part, the grounding end of the right front grounding part, the grounding end of the left rear grounding part and the grounding end of the right rear grounding part; the four pressure sensors are respectively a left front supporting leg grounding part grounding pressure sensor 1, a right front supporting leg grounding part grounding pressure sensor 2, a left rear supporting leg grounding part grounding pressure sensor 3 and a right rear supporting leg grounding part grounding pressure sensor 4;
the acquisition module, the tension sensor, the angle sensor and the four pressure sensors are respectively connected with the cloud platform through the NB-IOT transmission module; the cloud platform is connected with the mobile phone for early warning.
The combined crane anti-overturning detection system based on the cloud platform computing of the Internet of things has clear working principle. The dangerous state can be analyzed by utilizing the motion calculation, and the rollover early warning is realized.
A crane overturn prevention detection method based on an Internet of things cloud platform comprises the following steps:
s1, establishing a coordinate system;
s2, respectively acquiring data through the acquisition module, the tension sensor, the angle sensor and the four pressure sensors, and connecting the data with the cloud platform through the NB-IOT transmission module for analysis and judgment; and after the overturning condition is met, carrying out mobile phone early warning.
In step S1, the lowest point of the four legs of the crane is used as the origin O of the coordinate system, and the projection of the vertical axis of the level in the crane in the horizontal direction is the X axis, so that the four legs are distributed left and right, wherein the horizontal plane is the Z axis, the plane perpendicular to the XOZ plane is the Y axis, and the tilt amounts of the X and Y axes measured by the level are θ1，θ2The bubble direction of the level meter is the positive direction;
and changing the coordinate system into a Cartesian coordinate system through matrix transformation, wherein the left-hand rotation matrix of the crane moving in the Cartesian coordinate system is the actual motion state.
In the step S2, in the step S,
the pressure sensors below the four support legs send data information through the NB-IOT transmission module;
the weight of a heavy object hung by the drag hook is recorded as G through the tension sensor and is transmitted to the cloud platform through the NB-IOT transmission module, and the self weight of the crane is G1Decomposing on the X 'OY' plane, calculating the overturn of the X 'axis and the Y' axis,
the extension length of the extension arm is d, the distance between the left front leg and the right front leg is d1, the distance between the right front leg and the right rear leg is d2,
reading an angle beta between the extending arm and the Y' axis through the acquisition module, connecting the angle information and the gravity of the heavy object to the cloud platform through the NB-IOT transmission module, and analyzing the overturning of the crane through the cloud platform;
wherein, the analysis judgment mode is as follows:
the angle between the weight and the projecting arm is measured by the angle sensor as alpha, in the Y' axis direction, the projecting arm is | dcos β |,
when the cos beta of the cloud platform is positive, the gravity component is Gcos theta2The moment arm interval is
Figure BDA0002711607610000061
When in use
Figure BDA0002711607610000062
The supporting legs supported at the moment are a right front landing part and a right rear landing part, and when the pressure sensor of the landing part of the left front supporting leg and the pressure sensor of the landing part of the left rear supporting leg are detected to be 0, the crane is judged to overturn, and early warning is given out;
early warning of Y ' direction overturn, in the X ' axis direction, extending arm | dsin beta |, then analyzing on the X ' axis, the gravity component is Gcos theta1The extension arm is an X' axis component | dsin beta |, when the detected crane rotation angle beta data is transmitted to the cloud platform through the NB-IOT transmission module and is judged to be 0-180 degrees, the weight gravity component is Gcos theta1The moment arm interval is
Figure BDA0002711607610000063
The gravity component of the crane is G1cosθ1The gravity force arm of the crane is
Figure BDA0002711607610000064
When in use
Figure BDA0002711607610000065
When the pressure of the pressure sensor of the landing part of the left rear leg and the pressure sensor of the landing part of the right rear leg are 0, an X' axial overturn early warning is sent out;
when the detected crane rotation angle beta data is transmitted to the cloud platform through the NB-IOT transmission module and is judged to be 180 degrees and 360 degrees, the weight gravity component is Gcos theta1The distance between the force arms of the weights is
Figure BDA0002711607610000066
The gravity component of the crane is G1cosθ1The gravity force arm of the crane is
Figure BDA0002711607610000067
When in use
Figure BDA0002711607610000068
The supporting leg is a left rear supporting legThe landing part and the landing part of the right rear supporting leg detect the pressure sensor of the landing part of the left front supporting leg and the pressure sensor of the landing part of the right front supporting leg simultaneously, and when the pressures of the pressure sensor of the landing part of the left front supporting leg and the pressure sensor of the landing part of the right front supporting leg are 0, an overturning early warning is sent out.
Aiming at the defects that the reliability of four support legs of the existing crane is poor and the like when the four support legs are not positioned on the same plane, the invention provides a combined structure which utilizes the technology of Internet of things to collect the support pressure of the support legs and the work state during work, each support leg independently calculates the support force and transports the support force to the cloud platform of the Internet of things for calculation, so that reliable analysis of the motion state can be obtained, and the overturning risk is reduced. According to the invention, the data acquired by the sensor is transmitted to the cloud platform for overturning simulation calculation by utilizing NB-IOT internet of things data transmission, and when the calculation result shows that the overturning risk exists, early warning is carried out through the mobile phone end, so that the safety and the stability of the working operation of the crane on the inclined plane are improved.

Claims (4)

1. An intelligent folding arm crane safety early warning and control system based on cloud side end data fusion is characterized by comprising a crane system and a detection system, wherein the crane system comprises a base, a rotating assembly, a supporting leg assembly and an extending arm assembly,
the rotating assembly is arranged on the base and comprises a rotating platform,
the supporting leg assembly is arranged at two ends of the base and comprises four supporting legs which are respectively a left front supporting leg, a right front supporting leg, a left rear supporting leg and a right rear supporting leg,
the left front leg comprises a left front extension part and a left front ground falling part,
the right front leg includes a right front extension and a right front landing section,
the left rear leg comprises a left rear extension part and a left rear floor part,
the right rear leg comprises a right rear extension part and a right rear landing part,
the extension arm assembly is arranged on one side of the rotating platform and comprises an extension arm, a drag hook and a drag rope, and the drag hook is connected with the extension arm through the drag rope;
the detection system comprises a cloud platform, an acquisition module, an NB-IOT transmission module, a level meter, a tension sensor, an angle sensor and four pressure sensors,
the acquisition module is used for acquiring the motion state of the crane;
the gradienter is arranged on the rotating platform;
the tension sensor is arranged on the inhaul cable;
the angle sensor is used for acquiring an included angle between the inhaul cable and the extending arm;
the four pressure sensors are respectively arranged on the grounding end of the left front grounding part, the grounding end of the right front grounding part, the grounding end of the left rear grounding part and the grounding end of the right rear grounding part;
the acquisition module, the tension sensor, the angle sensor and the four pressure sensors are respectively connected with the cloud platform through the NB-IOT transmission module; the cloud platform is connected with the mobile phone for early warning.
2. A folding arm crane intelligent safety early warning and control method based on cloud side end data fusion is characterized by comprising the following steps:
s1, establishing a coordinate system;
s2, respectively acquiring data through the acquisition module, the tension sensor, the angle sensor and the four pressure sensors, and connecting the data with the cloud platform through the NB-IOT transmission module for analysis and judgment; and after the overturning condition is met, carrying out mobile phone early warning.
3. The intelligent folded jib crane safety early warning and control method based on cloud side end data fusion as claimed in claim 2,
in step S1, the lowest point of the four legs of the crane is used as the origin O of the coordinate system, and the projection of the vertical axis of the level in the crane in the horizontal direction is the X axis, so that the four legs are distributed left and right, wherein the horizontal plane is the Z axis, the plane perpendicular to the XOZ plane is the Y axis, and the tilt amounts of the X and Y axes measured by the level are θ1，θ2The bubble direction of the level meter is the positive direction;
and changing the coordinate system into a Cartesian coordinate system through matrix transformation, wherein the left-hand rotation matrix of the crane moving in the Cartesian coordinate system is the actual motion state.
4. The intelligent folded jib crane safety early warning and control method based on cloud side end data fusion as claimed in claim 3,
in the step S2, in the step S,
the pressure sensors below the four support legs send data information through the NB-IOT transmission module;
the weight of the heavy object lifted by the drag hook is marked as G through the tension sensor, and the self weight of the crane is G1Decomposing on the X 'OY' plane, calculating the overturn of the X 'axis and the Y' axis,
the extension length of the extension arm is d, the distance between the left front leg and the right front leg is d1, the distance between the right front leg and the right rear leg is d2,
reading an angle beta between the extending arm and the Y' axis through the acquisition module, connecting the angle information and the gravity of the heavy object to the cloud platform through the NB-IOT transmission module, and analyzing the overturning of the crane through the cloud platform;
wherein, the analysis judgment mode is as follows:
the angle between the weight and the projecting arm, downward along z, is measured by the angle sensor as α, and in the direction of the Y' axis, the projecting arm is | dcos β |,
when the cos beta of the cloud platform is positive, the gravity component is Gcos theta2The moment arm interval is
Figure FDA0002711607600000021
When in use
Figure FDA0002711607600000022
The supporting legs supported at the moment are a right front landing part and a right rear landing part, and when the pressure sensor of the landing part of the left front supporting leg and the pressure sensor of the landing part of the left rear supporting leg are detected to be 0, the crane is judged to overturn, and early warning is given out;
early warning of Y ' direction overturn, in the X ' axis direction, extending arm | dsin beta |, then dividing on the X ' axisThe gravity component is Gcos theta1The extension arm is an X' axis component | dsin beta |, when the detected crane rotation angle beta data is transmitted to the cloud platform through the NB-IOT transmission module and is judged to be 0-180 degrees, the weight gravity component is Gcos theta1The moment arm interval is
Figure FDA0002711607600000031
The gravity component of the crane is G1cosθ1The gravity force arm of the crane is
Figure FDA0002711607600000032
When in use
Figure FDA0002711607600000033
When the pressure of the pressure sensor of the landing part of the left rear leg and the pressure sensor of the landing part of the right rear leg are 0, an X' axial overturn early warning is sent out;
when the detected crane rotation angle beta data is transmitted to the cloud platform through the NB-IOT transmission module and is judged to be 180 degrees and 360 degrees, the weight gravity component is Gcos theta1The distance between the force arms of the weights is
Figure FDA0002711607600000034
The gravity component of the crane is G1cosθ1The gravity force arm of the crane is
Figure FDA0002711607600000035
When in use
Figure FDA0002711607600000036
The landing leg is left back landing leg portion and right back landing leg portion to support this moment, detects the pressure sensor of left front landing leg portion and the pressure sensor of right front landing leg portion simultaneously, and the pressure of the pressure sensor of left front landing leg portion and the pressure sensor of right front landing leg portion is 0, sends out the early warning that topples.
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Publication number Priority date Publication date Assignee Title
CN114803902A (en) * 2022-06-28 2022-07-29 江苏格雷特重工科技发展有限公司 Crane with anti-tipping regulation function
CN114803902B (en) * 2022-06-28 2022-09-20 江苏格雷特重工科技发展有限公司 Crane with anti-tipping regulation function

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